A Procedural Electroencephalogram Simulator for Evaluation of Anesthesia Monitors
Christian Leth Petersen1, Matthias Görges, Roslyn Massey
1From the *Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada; †Pediatric Anesthesia Research Team, Child and Family Research Institute, Vancouver, British Columbia, Canada; and ‡Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, British Columbia, Canada.
Anesthesia and Analgesia
|July 29, 2016
Summary
A new mobile app simulates electroencephalogram (EEG) signals to test anesthesia monitors. This method revealed significant differences in monitor performance, aiding the development of automated anesthesia systems.
Area of Science:
- Anesthesiology
- Biomedical Engineering
- Signal Processing
Background:
- Advances in anesthesia automation necessitate better understanding of electroencephalogram (EEG)-based endpoints.
- Current testing of anesthesia monitors is limited by the need for direct patient EEG data collection.
Purpose of the Study:
- To develop and validate a novel method for synthesizing EEG signals to test anesthesia monitors.
- To compare the performance of commercial anesthesia monitors using the developed simulation technology.
Main Methods:
- A mobile software application was developed to synthesize EEG signals at various depths of hypnosis.
- The simulator was used to generate functional monitor response profiles by systematic signal sweeps.
- Three commercial anesthesia monitors (Entropy, NeuroSENSE, and BIS) were evaluated.
Main Results:
- Significant variations in response and features were observed between the tested anesthesia monitors.
- Reproducible, nonmonotonic behavior and significant hysteresis were detected at light anesthesia levels.
- The simulator effectively revealed differences in the internal signal processing algorithms of commercial monitors.
Conclusions:
- Synthesizing EEG signals offers a new approach for systematically testing EEG-based monitors.
- This technology allows for comprehensive testing of anesthesia monitors and automated systems before human trials.
- The findings highlight the importance of standardized testing protocols for anesthesia monitoring devices.
